1 citations · 1 across the 7 of their papers we have counts for
9 papers
EpicWorldModel: Exploration-driven Planning with Latent World Models
Bowen Feng, Julian Ost, May Mei +2
Latent world models based on Joint-Embedding Predictive Architecture (JEPA) are deterministic by design. While successful in fully observable scenarios, this paradigm breaks down w…
ScenarioControl: Vision-Language Controllable Vectorized Latent Scenario Generation
Lili Gao, Yanbo Xu, William Koch +8
We introduce ScenarioControl, the first vision-language control mechanism for learned driving scenario generation. Given a text prompt or an input image, Scenario-Control synthesiz…
ChopGrad: Pixel-Wise Losses for Latent Video Diffusion via Truncated Backpropagation
Dmitriy Rivkin, Parker Ewen, Lili Gao +5
Recent video diffusion models achieve high-quality generation through recurrent frame processing where each frame generation depends on previous frames. However, this recurrent mec…
WorldFlow3D: Flowing Through 3D Distributions for Unbounded World Generation
Amogh Joshi, Julian Ost, Felix Heide
Unbounded 3D world generation is emerging as a foundational task for scene modeling in computer vision, graphics, and robotics. In this work, we present WorldFlow3D, a novel method…
LSD-3D: Large-Scale 3D Driving Scene Generation with Geometry Grounding
Julian Ost, Andrea Ramazzina, Amogh Joshi +3
Large-scale scene data is essential for training and testing in robot learning. Neural reconstruction methods have promised the capability of reconstructing large physically-ground…
VERDI: VLM-Embedded Reasoning for Autonomous Driving
Bowen Feng, Zhiting Mei, Julian Ost +5
While autonomous driving (AD) stacks struggle with decision making under partial observability and real-world complexity, human drivers are capable of applying commonsense reasonin…
Inverse Neural Rendering for Explainable Multi-Object Tracking
Julian Ost, Tanushree Banerjee, Mario Bijelic +1
Today, most methods for image understanding tasks rely on feed-forward neural networks. While this approach has allowed for empirical accuracy, efficiency, and task adaptation via…
Neural Point Light Fields
Julian Ost, Issam Laradji, Alejandro Newell +2
We introduce Neural Point Light Fields that represent scenes implicitly with a light field living on a sparse point cloud. Combining differentiable volume rendering with learned im…
Neural Scene Graphs for Dynamic Scenes
Julian Ost, Fahim Mannan, Nils Thuerey +2
Recent implicit neural rendering methods have demonstrated that it is possible to learn accurate view synthesis for complex scenes by predicting their volumetric density and color…